Hemicryptophytes Research Articles

Spatial (Mis)Matches Between Biodiversity and Habitat Quality Under Multi-Scenarios: A Case Study in Shandong Province, Eastern China

Despite declines in biodiversity and habitat quality (HQ) at a global scale, our understanding of the HQ and matches between HQ and biodiversity under management scenarios is incomplete. To address this deficiency, the study examined trends in HQ and (mis)matches between biodiversity and HQ over four decades in Shandong province, China, identified the key drivers, and assessed the effectiveness of ecological policies, including Ecological Redlines (ERLs) and the Grain for Green (GG) program. During the 40-year period, HQ and matching degrees (indicated by related coefficients) between biodiversity and HQ decreased obviously. Correlation analysis showed that related coefficients between HQ and four biodiversity indices (vertebrate, vascular plant, and vegetation formation type richness, and comprehensive biodiversity index) were all significant (p < 0.01), and coefficients were highest for the biodiversity composite index. An analysis of relative importance by the random forest algorithm indicated significant variation in driving factors for spatial distribution of HQ, biodiversity, and matches between them. The key determinants of biodiversity distribution were biophysical factors, such as NDVI (normalized difference vegetation index), DEM (digital elevation model), and temperature. However, the main drivers of HQ distribution were social factors, such as the accessibility of anthropogenic activities, urbanization, and population density. Ecological policy scenarios, ERLs and GG, are clearly effective and could improve HQ and the matching degree between HQ and biodiversity significantly. Furthermore, the improvement in HQ under ERLs was less than that under GG, while the increase in the matching degree was opposite. The results of this study can be integrated by ecological managers and planners for biodiversity conservation.

Comparative Evaluation of Spores and Vegetative Forms of Bacillus subtilis and Bacillus licheniformis on Probiotic Functionality In Vitro and In Vivo.

The probiotic effects of Bacillus are strain-specific and dependent on both spore and vegetative forms, but the distinct contributions of these forms to probiotic functionality are not well understood. This study aimed to evaluate and compare the impacts of vegetative forms and spores of Bacillus subtilis and Bacillus licheniformis on probiotic functions in vitro and in vivo. We systematically assessed the anaerobic metabolic capabilities and the potential to enhance the intestinal barrier function of four Bacillus strains, leading to the selection of Bacillus subtilis X22 and Bacillus licheniformis N-3 for detailed investigation. Utilizing in vitro fermentation with murine fecal microbiota, we observed that the spores form of Bacillus licheniformis N-3 noticeably positively regulated the gut microbiota under anaerobic conditions. Concurrently, both spore and vegetative forms of Bacillus licheniformis N-3 and Bacillus subtilis X22 demonstrated the ability to prevent pathogen adhesion, reduce inflammation, combat oxidative stress, and promote cellular autophagy to reduce apoptosis in response to enterotoxigenic Escherichia coli (ETEC) infection in the IPEC-J2 cell model. As a facultative anaerobe, Bacillus licheniformis N-3 exhibited a tendency toward superior regulatory capacity in enhancing the anti-infective activity of IPEC-J2 cells in vitro. In the pathogens challenge mouse model, B. licheniformis N-3 effectively preserved the integrity of jejunal tissue and enhanced the expression of glycoproteins in goblet cells. Moreover, B. licheniformis N-3 strengthened the epithelial barrier by increasing the levels of Occludin and Claudin-1 in the jejunum, thus promoting overall intestinal health. This research offers new insights into strain selection and the life cycle utilization of Bacillus probiotics.

Monitoring soil arsenic content in densely vegetated agricultural areas using UAV hyperspectral, satellite multispectral and SAR data

Accurate and effective monitoring of potentially toxic elements (PTEs) in soil across vast regions is crucial for environmental modeling and public health. While remote sensing (RS) technology provides a promising approach by detecting soil spectrum, dense and persistent vegetation cover in subtropical agricultural areas hinders acquisition of bare soil signals, limiting soil PTEs monitoring. To address this challenge, the present study proposed an innovative method for monitoring soil arsenic (As) content by using vegetation characteristics retrieved from RS data as proxy variables, given soil-vegetation interactions. The method was evaluated in a densely vegetated cropland of southern China, where 104 surface soil samples were collected. Vegetation information was extracted both individually and synergistically using time-series Sentinel-2 multispectral and Sentinel-1 synthetic aperture radar (SAR) images throughout the entire growing season, and an unmanned aerial vehicle (UAV) hyperspectral image during the crop maturity. Multiple machine learning algorithms, including Random Forest, Support Vector Regression, CatBoost, and Stacking were applied to model the relationship between soil As and vegetation variables. The SHapley Additive exPlanation (SHAP) technique was introduced for identifying key variables and corresponding thresholds indicating significant accumulation of soil As. Results showed that time-series satellite-multispectral images outperformed other single RS data types in terms of prediction accuracy. Moreover, the synergy of optical and SAR images significantly improved model accuracy. Particularly, the combination of time-series satellite multispectral and SAR data using the stacking algorithm achieved the best results, with a coefficient of determination (R2) of 0.71 and a root mean square error (RMSE) of 20.22 mg/kg. Key predictive variables included red-edge vegetation index (RENDVI3) on August 7 and May 26, and the blue band on October 26, with values below 0.018, 0.013 and 0.052, respectively, indicating the As accumulation in soil. In summary, the proposed method of using multiple RS data to retrieve vegetation characteristics for inferring soil PTEs in densely vegetated areas was convenient, cost-effective, and reliable, offering new insights and technical support for environmental monitoring.

Enhancing ice cream quality with dietary fiber and spore-forming probiotics: A study on Shouchella clausii and Heyndrickxia coagulans

This study aimed to assess the potential positive impact of incorporating milk fermented with dietary fiber (wheat fiber and inulin) and spore-forming probiotics (Shouchella clausii and Heyndrickxia coagulans) on ice cream quality during 90 days at −25 °C. Ice cream formulations combined fermented and non-fermented ingredients. Viable cell and spore counts, sensory, physical, chemical, and thermal properties, and energy content were analyzed. Probiotic cultures remained viable in both vegetative and spore forms. Throughout storage, probiotic ice creams with S. clausii showed higher viable cell counts (≥8.25 log CFU/g) than those with H. coagulans. Among formulations, inulin-enhanced S. clausii ice cream had the highest viability, maintaining the best survival rate on day 90. All samples received equivalent scores for general acceptability, with a mean score of 7.45 for taste and smell, indicating no compromise in sensory quality. The fibers increased viscosity, affected melting time, and influenced fat destabilization, with wheat fiber contributing to increased hardness. Probiotic ice creams, whether fiber-enriched or fiber-free, had balanced calorie content comparable to standard ice cream, indicating potential for healthier dessert options. These findings highlight the potential of spore-forming probiotics and dietary fibers in developing functional ice creams with health benefits and high sensory quality.

EDUTOURISM AS AN EFFORT TO STRENGTHEN KELAN VILLAGE RESILIENT AND PRO-ENVIRONMENTAL TOURISM VILLAGE

Kelan Tourism Village is located in Kuta District, Badung Regency, Bali Province, and has the potential for marine tourism and culinary tourism by utilizing sea products in the form of seafood as the main menu. This tourism potential is currently underway, but economically it has not yet had a maximum impact, as a result of the existence of complementary products in the form of vegetables to complement the seafood menu which are still purchased from outside the Kelan Tourism Village, even though the plantation area is still available. Based on these problems, the solution provided is the application of the Biofloc Aquaponics Integrated Urban Farming Model, Drip Irrigation Vegetable Garden Tilapia which is packaged as edutourism, targeting elementary school students, middle school students, tourists/visitors, and the Kelan Tourism Village community. The implementation of the solution shows that there has been an increase in understanding, knowledge and skills of the target groups, namely elementary school students, junior high school students, tourists/visitors and the community regarding Integrated Urban Farming Aquaponics Biofloc, Tilapia Fish Garden Vegetable Drip Irrigation. Apart from that, people involved in culinary tourism also experienced an increase in income, as a result of reduced purchases of complementary products in the form of vegetables that they were able to produce themselves, as well as strengthening environmental conservation.

Areas and Resources of the Satureja L. Genus in Nakhchivan (Azerbaijan)

The study of the habitats and resources of 4 species of Satureja: Satureja hortensis L., S. laxiflora K. Koch, S. macrantha C. A. Mey. and S. mutica Fisch. et C. A. Mey. from the Lamiaceae family being a valuable essential oil plant. S. macrantha previously, single specimens were found in the Kyzylkaya and Negram-Dorosham mountains. 2018 we managed to identify the mountains of Darydag of Julfa district. In 2018, we managed to develop the Darydag, then 4 new locations in Mamadein, Keleki, Damir and Lalali mountain in the Ordubad district (1400–2800 m). Here Satureja grandiflora forms hitherto undescribed formations and associations covering vast rocky areas. S. laxiflora and S. mutica are newly identified species. It has been established that this species is a spinning, essential oil, medicinal and anti-erosion plant. We studied environmental conditions, the role in the formation of rock-talus vegetation in the region, economic importance, rational use and protection. We recommend expedient, planned and reasonable use of natural resources, the species of Satureja laxiflora, S. grandiflora, will expand crops, plantations of the cultivated species S. hortensis L.

Implications of leaf burning for adverse respiratory conditions and release of fine particulates and air pollutants

The residential burning of leaves, brush, grass, and other forms of vegetation are major and underappreciated source of particulates smaller than 2.5 μm (PM2.5), carbon monoxide, and many other air pollutants including carcinogenic polycyclic hydrocarbons such as benzo(a)pyrene. Residential leaf burning has been linked to significantly poorer urban/suburban air quality, respiratory morbidity and mortality, serious burn injuries to people, and property damage. Other forms of biomass burning such as wildfires, wood burning, peatland wildfires, and the deliberate burning of woodlands and agricultural fields produce large amounts of air pollutants, which are somewhat similar in composition to those released from leaf burning. Leaf burning has been linked to significantly higher rates of asthma and other respiratory problems. Exposure to wildfire smoke has been linked to significantly higher rates of cancer, infections, and a wide range of health conditions including respiratory, cardiovascular, psychiatric, and reproductive problems. Leaf burning and other forms of biomass burning produce significant quantities of dark particulates that accelerate global warming. Leaf burning also presents serious risk of burn injuries to humans, wildlife, and buildings. A number of U.S. states and European Countries have imposed total state or national bans on leaf burning. In fact, many communities offer free or inexpensive community leaf pickup and composting services. Leaf composting offers many advantages over leaf burning; for instance, leaf compost is a valuable product useful for growing plants. In conclusion, homeowners, communities, and nations should compost leaves, brush, and grass clippings rather than burning them.

Methods for Extracting Fractional Vegetation Cover from Differentiated Scenarios Based on Unmanned Aerial Vehicle Imagery

Fractional vegetation cover (FVC) plays a key role in ecological and environmental status assessment because it directly reflects the extent of vegetation cover and its status, yet vegetation is an important component of ecosystems. FVC estimation methods have evolved from traditional manual interpretation to advanced remote sensing technologies, such as satellite data analysis and unmanned aerial vehicle (UAV) image processing. Extraction methods based on high-resolution UAV data are being increasingly studied in the fields of ecology and remote sensing. However, research on UAV-based FVC extraction against the backdrop of the high soil reflectance in arid regions remains scarce. In this paper, based on 12 UAV visible light images in differentiated scenarios in the Ebinur Lake basin, Xinjiang, China, various methods are used for high-precision FVC estimation: Otsu’s thresholding method combined with 12 Visible Vegetation Indices (abbreviated as Otsu-VVIs) (excess green index, excess red index, excess red minus green index, normalized green–red difference index, normalized green–blue difference index, red–green ratio index, color index of vegetation extraction, visible-band-modified soil-adjusted vegetation index, excess green minus red index, modified green–red vegetation index, red–green–blue vegetation index, visible-band difference vegetation index), color space method (red, green, blue, hue, saturation, value, lightness, ‘a’ (Green–Red component), and ‘b’ (Blue–Yellow component)), linear mixing model (LMM), and two machine learning algorithms (a support vector machine and a neural network). The results show that the following methods exhibit high accuracy in FVC extraction across differentiated scenarios: Otsu–CIVE, color space method (‘a’: Green–Red component), LMM, and SVM (Accuracy > 0.75, Precision > 0.8, kappa coefficient > 0.6). Nonetheless, higher scene complexity and image entropy reduce the applicability of precise FVC extraction methods. This study facilitates accurate, efficient extraction of vegetation information in differentiated scenarios within arid and semiarid regions, providing key technical references for FVC estimation in similar arid areas.

Diet of Andean Leaf-Eared Mice (Phyllotis) Living at Extreme Elevations on Atacama Volcanoes: Insights From Metagenomics, DNA Metabarcoding, and Stable Isotopes.

On the flanks of > 6000 m Andean volcanoes that tower over the Atacama Desert, leaf-eared mice (Phyllotis vaccarum) live at extreme elevations that surpass known vegetation limits. The diet of these mice in these barren, hyperarid environments has been the subject of much speculation. According to the arthropod fallout hypothesis, sustenance is provided by windblown insects that accumulate in snowdrifts ("aolian deposits"). Mice may also feed on saxicolous lichen or forms of cryptic vegetation that have yet to be discovered at such high elevations. We tested hypotheses about the diet of mice living at extreme elevations on Atacama volcanoes by combining metagenomic and DNA metabarcoding analyses of gut contents with stable isotope analyses of mouse tissues. Genomic analyses of contents of the gastrointestinal tract of a live-captured mouse from the summit of Volcán Llullaillaco (6739 m) revealed an opportunistic but purely herbivorous diet, including lichens. Although we found no evidence of animal DNA in gut contents of the summit mouse, stable isotope data indicate that mice from elevations at or near vegetation limits (~5100 m) include a larger fraction of animal prey in their diet than mice from lower elevations. Some plant species detected in the gut contents of the summit mouse are known to exist at lower elevations at the base of the volcano and in the surrounding Altiplano, suggesting that they may occur at higher elevations beneath the snowpack or in other cryptic microhabitats.

Mapping Leaf Mass Per Area and Equivalent Water Thickness from PRISMA and EnMAP

With the continued advancement of spaceborne hyperspectral sensors, hyperspectral remote sensing is evolving as an increasingly pivotal tool for high-precision global monitoring applications. Novel image spectroscopy data, e.g., the PRecursore IperSpettrale della Missione Applicativa (PRISMA) and Environmental Mapping and Analysis Program (EnMAP), can rapidly and non-invasively capture subtle spectral information of terrestrial vegetation, facilitating the precise retrieval of the required vegetation parameters. As critical vegetation traits, Leaf Mass per Area (LMA) and Equivalent Water Thickness (EWT) hold significant importance for comprehending ecosystem functionality and the physiological status of plants. To address the demand for high-precision vegetation parameter datasets, a hybrid modeling approach was proposed in this study, integrating the radiative transfer model PROSAIL and neural network models to retrieve LMA and EWT from PRISMA and EnMAP images. To achieve this objective, canopy reflectance was simulated via PROSAIL, and the optimal band combinations for LMA and EWT were selected as inputs to train neural networks. The evaluation of the hybrid inversion models over field measurements showed that the RMSE values for the LMA and EWT were 4.11 mg·cm−2 and 9.08 mg·cm−2, respectively. The hybrid models were applied to PRISMA and EnMAP images, resulting in LMA and EWT maps displaying adequate spatial consistency, along with cross-validation results showing high accuracy (RMSELMA = 5.78 mg·cm−2, RMSEEWT = 6.84 mg·cm−2). The results demonstrated the hybrid inversion model’s universality and applicability, enabling the retrieval of vegetation parameters from image spectroscopy data and offering a valuable contribution to hyperspectral remote sensing for vegetation monitoring, though the availability of field measurement data remained a significant challenge.

The RARCrec: A rapid riparian vegetation assessment method for use in river systems undergoing vegetative and geomorphic recovery

SummaryMonitoring the condition of returning vegetation over time is essential for effectively managing riparian vegetation. Rapid riparian assessment methods are standard tools for capturing a suite of variables relevant to river health and are accessible to a range of users with different levels of experience. Monitoring efforts are particularly important for rivers undergoing degrading impacts and subsequent management interventions. In coastal catchments of New South Wales, Australia, vegetation is returning to rivers that were historically cleared for agriculture and are now experiencing geomorphic recovery. We present a rapid riparian assessment method for rivers undergoing vegetative and geomorphic recovery in this region. It addresses a gap in available rapid assessments by providing a methodology that can be used at sites with no historical analogue. Our assessment method adapts and extends a widely used method called the Rapid Assessment of Riparian Condition (RARC) to capture the quality of returning riparian vegetation along recovering rivers (rec), including native species diversity and vegetation structure (hence the name RARCrec). The RARCrec incorporates four sub‐indices – vegetation cover, native species richness, proportion of native to exotic species, and features of vegetation health – to produce an overall vegetation condition score that classifies sites as poor, moderate, or good condition. Scores for each sub‐index are assessed for the vegetation strata (groundcover, graminoids, midstorey, vines, and canopy) on the landform units of river bars, benches, and floodplains. The RARCrec has been designed to be sufficiently general for use in the main Vegetation Formations in coastal New South Wales and has been trialled at 36 sites across this region. Assessments can be conducted within half a day by two technically competent users and can be used to monitor vegetation condition over time to inform where to prioritise implementation of management activities. Field methodology and data sheets, including a scoring system, are provided to support the implementation of the RARCrec.

Optimizing key parameters (biological-control factor) of soil erosion simulation models at a regional scale– The case of Jiangxi Province, China

Unveiling the spatial information of actual soil erosion is a prerequisite for subsequent soil erosion research and is critical for soil and water conservation as well as ecological resource protection. However, the existing regional-scale soil erosion simulation models often ignore the vertical structure of vegetation, particularly near-surface vegetation information, which leads to discrepancies with the real-world conditions. This study aims to optimize the biological-control factor (B factor) of the Chinese Soil Loss Equation (CSLE) model to improve simulation accuracy. The Global Ecosystem Dynamics Investigation (GEDI) can provide accurate layered vegetation data. Thus, this study focuses on the forest of Jiangxi Province, simulating the understory vegetation structure by vegetation type using a combination of GEDI data and sampled data. By considering the soil and water conservation benefits of different vegetation layers, we developed a B factor optimization method to simulate soil erosion in forests at a regional scale. Compared to previous methods, the optimized B factor mean value for Jiangxi Province’s forested areas increased from 0.0034 to 0.0096. The estimated soil erosion changed from 38 t·km-2a-1 (with 86.6 % of forests exhibiting no soil erosion) to 166.7t·km-2a-1 (with 28.2 % of forests exhibiting no soil erosion). Our findings indicate that the optimized assessment results are more consistent with the actual situation. The optimization method is a good attempt at regional-scale B factor simulation and can provide a more accurate depiction of the spatial information of soil erosion in forest at the regional scale. This study can lay a solid foundation for future regional-scale soil erosion assessments and offer valuable data support and methodological references for the regional-scale dynamic monitoring of soil and water loss, as well as research in soil and water conservation.

Calcium sorption and isotope fractionation in Bacillus subtilis and Pseudomonas aeruginosa

Bacteria are a key component of the critical zone, because of their role in the nutrient availability for the vegetation. There is still little knowledge on the direct role of bacteria on Ca storage/leaching in soils while it is an essential macronutrient for vegetation growth. In recent years, Ca stable isotopes have shown their potential in understanding the Ca biogeochemical cycle. Preliminary studies highlighted that in the presence of soil bacteria, the plant uptake of nutrients is increased due to the mineral bioweathering. Moreover, Ca isotope signatures of nutrient media also showed differences between growth experiments in batch in the presence and absence of bacteria. In this study, the focus is to verify if Ca adsorption and incorporation into/onto bacterial strains induce such isotopic fractionation. Batch experiments were carried out on Pseudomonas aeruginosa (a Gram-negative bacterium) and on the vegetative and sporulated forms of Bacillus subtilis (a Gram-positive bacterium). These experimentations showed that: (i) no observable isotopic fractionations were induced during calcium/bacteria contact for all experimental parameters (pH, kinetic, bacterial cell number, interaction time, dead/alive bacteria); (ii) Ca was mainly stored in the bacterial cell wall compartments. On the other hand, significant Ca isotopic differences between the spores and the sporulation medium (Δ44/40Caspores–sporulation medium ranging from − 0.53 to − 1.15‰), suggest isotopic fractionation during the sporulation process, likely occurring during the attachment of Ca to carboxyl acid groups as calcium chelates with dipicolinic acid. The absence of Ca isotope fractionation during Ca sorption on vegetative and sporulated bacteria via passive channels indicates that the tested bacteria’s contribution to the Ca biogeochemical cycle is indirect primary enhancing bioweathering and Ca bioavailability for vegetation. If confirmed by further studies, only the sporulation mechanisms itself may directly impact the Ca biogeochemical cycle.

Advancing streamflow prediction in data-scarce regions through vegetation-constrained distributed hybrid ecohydrological models

Hybrid models that combine deep learning with physical principles have recently shown significant promise in improving streamflow prediction in data-scarce regions, achieving generally greater accuracy and reliability than either method alone. However, existing hybrid hydrological models underutilize the extensive and readily available remote sensing data on vegetation, which plays a critical role in hydrological processes. Incorporating vegetation information can better constrain model processes by accounting for the interactions and feedbacks between vegetation and hydrology, thereby enabling more robust predictions. In this context, we present a novel distributed hybrid ecohydrological model that integrates dynamic vegetation processes into a distributed hybrid hydrological model, capable of simultaneously simulating leaf area index (LAI) and streamflow through multi-task learning. Our results indicate that in scenarios with limited available streamflow data, the combined constraint of LAI spatiotemporal patterns and streamflow significantly enhances the model’s ability to generalize streamflow simulation across space and time compared to models trained solely with either LAI or streamflow. Even with the increased availability of streamflow data, models utilizing both LAI and streamflow continue to exhibit superior robustness in streamflow prediction. The distributed ecohydrological model, which employs multi-process coupling and multi-source data constraints, accurately simulates the target variables (i.e., streamflow and LAI) while reliably capturing dynamic changes in other ecohydrological processes, such as evapotranspiration. This capability highlights its potential for multi-process diagnostics. Overall, our approach offers a new perspective for streamflow prediction in data-scarce regions and represents an important step towards integrating observational constraints from multiple subsystems into hybrid Earth system modeling.

The influence of soil factors on the different vegetation formations of the Dunas Park, Salvador, Bahia, Brazil

This article was conducted in a restinga ecosystem on quaternary sandy deposits of Parque das Dunas, Salvador, Bahia, Brazil; located north of Salvador, this area comprises a landscape formed by different edaphic gradients with varied vegetation formations. An edaphic characterization of the sections of these remnants was carried out to understand the influence of edaphic factors on the distribution of the plant composition of this environment. For this purpose, a transect was delimited perpendicular to the coastline. In this transect, 08 plots of 25x25m were implanted, 100m apart. In the Centre of each plot, a 1m wide and 60 cm deep trench was opened, where soil samples were collected to determine edaphic and granulometric parameters. These samples in each plot followed the distribution of the vegetation formations of this environment. It was found that the different water regimes and topography of the area influence the soil factors, which interferes with the distribution and heterogeneity of the vegetation. The highest levels of fine, very fine and medium sand fractions and calcium and phosphorus were found in the highest portions. These areas, with better drainage, have a higher plant density. There is a lower vegetation density with open sandbanks in lower areas, lower levels of fine, very fine and medium sand fractions, and lower nutrient retention. In these environments, some areas are partially flooded with adapted species. It was also found that most of the plots had a very acidic pH with the presence of exchangeable Al, which could indicate high nutrient unavailability. Thus, the sandbanks' soil conditions influence the vegetation's development, inducing the plant species to develop adaptive mechanisms to maintain their biological organization.

Study and Notes for the Freshwater Spercheidae, Dryopidae and Heteroceridae (Coleoptera) Fauna of Erzurum Province: A New Record for Türkiye

In this study, samples of Dryopidae, Heteroceridae and Spercheidae (Coleoptera) were collected from the shallow areas of lakes, ponds, rivers and small puddles in Erzurum province (Türkiye) between 2015 and 2020 with sieves of 3.15 x 1 mm pore size (mesh size 500 µm). A total of 4 different species were found. Two individuals from Dryops griseus (Erichson, 1847) species; 1 individual from the species Dryops jeanneli Bollow 1938; 2 individuals of Heterocerus fenestratus Thunberg 1784; and 2 individuals of Spercheus emarginatus (Schaller, 1783) species were caught. The collected samples were evaluated based on their morphological and ecological characteristics. While D. griseus was recorded for the first time in Türkiye, D. jeanneli and S. emarginatus are the third examples of species recorded in Türkiye. Additionally, these two species were recorded for the first time in the Eastern Anatolia region. H. fenestratus, collected from the Eastern Anatolia Region by another researcher, was also found during the study. The lateral parameters of the species' aedeagophores collapse from the middle towards the interior. Aedeagophore photographs and distribution data in the country and worldwide are discussed in the article. The average temperature and chemical parameters (electrical conductivity, pH, total nitrogen, dissolved oxygen, total phosphorus and water temperature) of the water bodies where the four different species were collected were found to be close to each other. To comprehend the life cycle, ecological data, along with morphological descriptions and vegetation information for each species are described.

Beyond information: The power of personalized nudges in promoting vegetable purchases

This study explores the impact of providing general health-related information and personalized nudges aimed at modifying cognitive biases on enhancing vegetable purchases and consumption. We conducted a four-month natural field experiment and analyzed daily purchase records of 942 households using receipt scanner data. While merely explaining the loss-framed health benefits of vegetables did not significantly alter the overall vegetable purchasing habits, we observed a notable decrease in meat purchases, attributing this to the indirect effects of vegetable information. Additionally, when the status of relative vegetable purchases amount was provided based on personal purchase histories, individuals who initially purchased more vegetables demonstrated an increased buying volume. This effect was more pronounced in households with children than in those without. The nudging interventions had long-term effects beyond the experiment’s duration, possibly driven by an altruistic concern for children’s health within the household. Therefore, while nudges alone are not a complete solution, their ability to effect long-term changes in household purchasing patterns suggests that they can be a valuable addition to policy tools promoting sustainable and healthy food choices, as well as traditional mass-targeted promotion strategies.

Mural infectious endocarditis in a patient with tetralogy of Fallot: a clinical case

The article presents a clinical case of development of mural infective endocarditis (IE) with formation of vegetations in the region of the upper third of the interventricular septum in patient A., 51 years old, with uncorrected tetralogy of Fallot. The patient was admitted with complaints of increased heart rate, interruptions in the heart work, feet swelling, shins up to the upper third, dyspnea at rest, general weakness, fever up to 39 оC, sweating, headache. During transthoracic echocardiography on the upper third of the interventricular septum (IVS) from the side of the RV, an additional echo-positive linear mobile formation 0.9 cm long is visualized, similar to the chords of the tricuspid valve. Thus, based on the identification of 1 major Duke criterion (imaging criterion — the presence of parietal vegetation) and 3 minor criteria (predisposing factors — congenital heart disease of the blue type; fever >38 оC; positive blood culture not meeting the requirements for the major criterion), laboratory and instrumental diagnostic data and anamnesis, the following diagnosis was established: "Secondary infective endocarditis with damage to the upper third of the interventricular septum". Taking into account the sensitivity of the identified microflora, polymyxin and moxifloxacin were prescribed. During therapy, a dry cough and dry wheezing in the projection of the middle lobe on the right appeared. To exclude septic embologenic pneumonia, computed tomography of the chest organs was performed, on which no focal/infiltrative changes were detected. However, a shunt connecting the brachiocephalic trunk with the right pulmonary artery was visualized, which may explain the cause of compensation of hypoxemia that arose due to pathological hemodynamics as a result of high pulmonary stenosis. Given the incomplete effectiveness of therapy, as well as the sensitivity of the infectious agents isolated, a decision was made to change antibacterial therapy to vancomycin in combination with imipenem. Conservative treatment methods allowed not only to compensate for the existing clinical symptoms, but also to achieve reference values of laboratory parameters, despite the impossibility of surgical intervention.

Are the ecological benefits of hydrological connectivity projects continuously increasing? Insights from the perspective of landscape patterns − ecosystem processes − ecosystem services

The construction of hydrological connectivity projects alters the natural morphology and hydrological rhythms of the basin, which can subsequently impact ecological processes and ecosystem services. Quantifying the impacts of hydrological connectivity projects on ecosystems is fundamental for providing theoretical support to researchers and policy makers. Ecological water conveyance projects (EWCP) aimed at ecological restoration are one type of hydrological connectivity projects. In this study, a multi-dimensional hydrological connectivity assessment framework is established to quantify the impacts of the EWCP on landscape patterns. Analytic Hierarchy Process − Entropy Method (AHP-EM) is used to calculate the integrated hydrological connectivity index (IHCI). Ecosystem processes are characterized by vegetation indexes and ecological indexes. The ecosystem services are quantified by ecosystem service value (ESV). An improved ESV calculation method is proposed to assess the ecological benefits of EWCP. This method not only captures the spatial heterogeneity information of land use, vegetation and ecological conditions but also integrates socioeconomic factors. The relationships between trade-offs and synergies among provisioning, regulating, supporting and cultural ecosystem services are clarified to optimize the overall benefits. The results show that hydrological connectivity increases consistently with ecological water conveyance volume (EWCV). ESV is increased positively with IHCI and it shows a correlation with the distance to the riverbank. A new finding is that the ecological benefit shows an inflection point in 2010, which conforms to the “marginal benefit decreasing law”. These results provide a new insight on hydrological connectivity dynamics under the influence of EWCP, and the finding has guiding significance for efficient utilization of water resources in EWCP. The methodologies used in this research can be widely applied to other EWCPs.

Assessing the Potential of UAV for Large-Scale Fractional Vegetation Cover Mapping with Satellite Data and Machine Learning

Fractional vegetation cover (FVC) is an essential metric for valuating ecosystem health and soil erosion. Traditional ground-measuring methods are inadequate for large-scale FVC monitoring, while remote sensing-based estimation approaches face issues such as spatial scale discrepancies between ground truth data and image pixels, as well as limited sample representativeness. This study proposes a method for FVC estimation integrating uncrewed aerial vehicle (UAV) and satellite imagery using machine learning (ML) models. First, we assess the vegetation extraction performance of three classification methods (OBIA-RF, threshold, and K-means) under UAV imagery. The optimal method is then selected for binary classification and aggregated to generate high-accuracy FVC reference data matching the spatial resolutions of different satellite images. Subsequently, we construct FVC estimation models using four ML algorithms (KNN, MLP, RF, and XGBoost) and utilize the SHapley Additive exPlanation (SHAP) method to assess the impact of spectral features and vegetation indices (VIs) on model predictions. Finally, the best model is used to map FVC in the study region. Our results indicate that the OBIA-RF method effectively extract vegetation information from UAV images, achieving an average precision and recall of 0.906 and 0.929, respectively. This method effectively generates high-accuracy FVC reference data. With the improvement in the spatial resolution of satellite images, the variability of FVC data decreases and spatial continuity increases. The RF model outperforms others in FVC estimation at 10 m and 20 m resolutions, with R2 values of 0.827 and 0.929, respectively. Conversely, the XGBoost model achieves the highest accuracy at a 30 m resolution, with an R2 of 0.847. This study also found that FVC was significantly related to a number of satellite image VIs (including red edge and near-infrared bands), and this correlation was enhanced in coarser resolution images. The method proposed in this study effectively addresses the shortcomings of conventional FVC estimation methods, improves the accuracy of FVC monitoring in soil erosion areas, and serves as a reference for large-scale ecological environment monitoring using UAV technology.